Jump to content

Lernmatrix

From Wikipedia, the free encyclopedia
The printable version is no longer supported and may have rendering errors. Please update your browser bookmarks and please use the default browser print function instead.

Lernmatrix (German for "learning matrix") is a special type of artificial neural network (ANN) architecture, similar to associative memory, invented around 1960 by Karl Steinbuch, a pioneer in computer science and ANNs.[1]

This model for learning systems could establish complex associations between certain sets of characteristics (e.g., letters of an alphabet) and their meanings.

Function

The Lernmatrix generally consists of n "characteristic lines" and m "meaning lines," where each characteristic line is connected to each meaning line, similar to how neurons in the brain are connected by synapses. (This can be realized in various ways – according to Steinbuch, this could be done by hardware or software).

To train a Lernmatrix, values are specified on the corresponding characteristic and meaning lines (binary or real); then the connections between all pairs of characteristic and meaning lines are strengthened by the Hebb rule. A trained Lernmatrix, when given a specific input on the characteristic lines, activates the corresponding meaning lines. In modern language, it is a linear projection module.

By appropriately interconnecting several Lernmatrices, a switching system can be built that, after completing certain training phases, is ultimately able to automatically determine the most probable associated meaning for an input sequence of features.[2]

See also

Further reading

  • Karl Steinbuch: Automat und Mensch. 1st ed. Springer 1961. (in German)

References

  1. ^ Steinbuch, Karl (1961). "Die Lernmatrix". Kybernetik, 1(1):36-45.
  2. ^ Karl Steinbuch – Informatiker der ersten Stunde at edoc.hu-berlin.de, accessed on March 1, 2015.